Training Custom object detection network using tensor-flow object detection API?
I have found a hack to integrate keras with tensorflow object detection API. This hack works if you have trained the keras classification model with tensorflow backend. If above is the case you can extend the classification model to a object detection model by first converting the keras checkpoint to a tensorflow checkpoint then in the object detection API write new feature extractor layers using tf.keras (Keras is now part of core tensorflow starting from version 1.4). you can simply copy paste your layer definitions and pass the path to the converted checkpoint in the config file and it will work.